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Long circulating RNAs identified as biomarker candidates for risk stratification in childhood acute lymphoblastic leukemia

GSE245139 Homo sapiens (human) RNA-seq (gene expression) 45 samples Submitted 2025/04/30 Platform GPL18573Platform GPL20301
At a glance

RNA-seq (gene expression) · human · 45 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Topic
Acute lymphoblastic leukemiaThis series is part of our curated briefing on it.
Samples
45 samples: 5 conditions, mostly with about 12 replicates eachGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
Long Circulating RNAs Packaged in Extracellular Vesicles: Prospects for Improved Risk Assessment in Childhood B-Cell Acute Lymphoblastic LeukemiaInternational journal of molecular sciences · 2025
Summary (written by the submitters)
Analysis of tumoral RNA is essential for childhood acute lymphoblastic leukemia (ALL) diagnosis and prognosis to detect mutations, cryptic fusions and gene expression patterns. Small vesicles circulating in the blood, such as exosomes carry nucleic acids that might be involved in cancer formation and progression, thus presenting a potential for discovery of non-invasive biomarker for diagnosis and monitoring.
Read the full summary ↓
Here we report the identification of 47 circulating exosome-encapsulated RNA transcripts (30 mRNAs, 5 lncRNAs, 9 circRNAs and 3 pseudogenes) constituting putative biomarker in 2 molecular subgroups of childhood ALL patients. Exosomes were purified from peripheral blood collected at diagnosis from 10 patients positive for the ETV6-RUNX1 and TCF3-PBX1 fusions as well as from conditioned culture medium (CCM) of their representative cell models. Long transcriptome profiling via total RNA sequencing, supported by the implementation of a novel data analysis pipeline confirmed the presence of mRNAs, fusion transcripts, long non-coding and circular RNAs in exosomes. Differential expression analysis comparing tumoral and exosomal RNA revealed 2 transcripts enriched in both leukemic subtypes while 38 were exclusively enriched in ETV6-RUNX1+ patients and 7 were exclusively enriched in TCF3-PBX1+ patients. These are the first results highlighting specific enrichment of long RNA transcripts in exosomes among two distinct ALL subtypes, suggesting the need for investigation of larger cohorts to identify and validate novel circulating biomarkers.
Published in
Long Circulating RNAs Packaged in Extracellular Vesicles: Prospects for Improved Risk Assessment in Childhood B-Cell Acute Lymphoblastic Leukemia
Poncelet L, Richer C, Gutierrez-Camino A et al. · International journal of molecular sciences 2025 · PMID 40362196 · doi:10.3390/ijms26093956
This dataset
Open GSE245139 in finder → Find more human RNA-seq datasets → Acute lymphoblastic leukemia landscape →
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE245139_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1026997 and SRA study SRP465797. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40362196) ↗
Study design
5 conditions, mostly with about 12 replicates each
Tumor - ETV6-RUNX1+ patient ×12 Tumor - TCF3-PBX1+ patient ×12 Exosomes purified from peripheral blood - ETV… ×5 Exosomes purified from peripheral blood - TCF… ×5 CD10+/CD19+ B Cell Control ×3 697 whole cells extract ×1 697 CCM derived microvesicles ×1 697 CCM derived small extracellular vesicles ×1 +5 more

Supports a case/control comparison: 34 samples read as cases, 3 as controls.

How we read this: 5 replicated groups read from 45 sample titles; they account for 37 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

+ 5 more — browse all 45 samples with per-sample file links →

More Acute lymphoblastic leukemia datasets

Search all human RNA-seq datasets in GEO →

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